Abstract
With the continuous improvement of China’s economic level, the research of economic data management has been paid more and more attention. As the high-tech industry plays an increasingly important role in the world economy, it has become a strategic highland for all countries in the world. How to design an economic data management model that integrates data mining techniques to achieve deep data mining and efficient utilization has become a research focus. In order to study the technical selection model of economic data, a new economic data management model based on a data mining algorithm is proposed. In the study of economic management data, the optimization model of data management is designed based on computer technology. In the optimization of data classification, a data mining algorithm is adopted to fully realize the reasonable management of data. According to the principle of the Random Dynamic Optimization Algorithm, the algorithm is improved, and its convergence speed is accelerated. The improved algorithm is applied to solve the one-dimensional cutting problem. Compared with other algorithms, the conversion method greatly improves the utilization rate of raw materials. Then, the efficiency and adaptability of the algorithm are tested by determining the algorithm and applying it to the knapsack problem.
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More From: International Journal of High Speed Electronics and Systems
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